Imperial College London
Alternate

Professor Paul M. Matthews

Faculty of Medicine, Department of Brain Sciences

Edmond and Lily Safra Chair, Head of Department
 
 
 
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Contact

 

+44 (0)20 7594 2855p.matthews

 
 
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Assistant

 

Ms Siobhan Dillon +44 (0)20 7594 2855

 
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Location

 

E502Burlington DanesHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Robinson:2017:10.1007/978-3-319-66182-7_82,
author = {Robinson, R and Valindria, V and Bai, W and Suzuki, H and Matthews, P and Page, C and Rueckert, D and Glocker, B},
doi = {10.1007/978-3-319-66182-7_82},
pages = {720--727},
publisher = {Springer},
title = {Automatic quality control of cardiac MRI segmentation in large-scale population imaging},
url = {http://dx.doi.org/10.1007/978-3-319-66182-7_82},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - The trend towards large-scale studies including population imaging poses new challenges in terms of quality control (QC). This is a particular issue when automatic processing tools such as image segmentation methods are employed to derive quantitative measures or biomarkers for further analyses. Manual inspection and visual QC of each segmentation result is not feasible at large scale. However, it is important to be able to detect when an automatic method fails to avoid inclusion of wrong measurements into subsequent analyses which could otherwise lead to incorrect conclusions. To overcome this challenge, we explore an approach for predicting segmentation quality based on reverse classification accuracy, which enables us to discriminate between successful and failed cases. We validate this approach on a large cohort of cardiac MRI for which manual QC scores were available. Our results on 7,425 cases demonstrate the potential for fully automatic QC in the context of large-scale population imaging such as the UK Biobank Imaging Study.
AU  - Robinson,R
AU  - Valindria,V
AU  - Bai,W
AU  - Suzuki,H
AU  - Matthews,P
AU  - Page,C
AU  - Rueckert,D
AU  - Glocker,B
DO  - 10.1007/978-3-319-66182-7_82
EP  - 727
PB  - Springer
PY  - 2017///
SN  - 0302-9743
SP  - 720
TI  - Automatic quality control of cardiac MRI segmentation in large-scale population imaging
UR  - http://dx.doi.org/10.1007/978-3-319-66182-7_82
UR  - http://hdl.handle.net/10044/1/49164
ER  -
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